Paper: arXiv 2609.02660

Authors: Vladimír Holý

Abstract

Trade durations in high-frequency foreign exchange data exhibit increased occurrence near integer values. To address this empirical phenomenon, we propose the granularity-adjusted autoregressive conditional duration (GA-ACD) model. It is based on a novel two-component mixture distribution consisting of a standard generalized gamma component for regular durations and a second component that locally redistributes probability mass around integer values to capture heaping. Conditional dynamics are modeled within a score-driven framework, allowing the scale parameter to vary over time in response to past durations, and enabling maximum likelihood estimation of all model parameters. A simulation study shows that ignoring heaping leads to biased parameter estimates and distorted inference regarding both the distribution and the dynamics of durations. An empirical analysis demonstrates that integer-duration clustering is pervasive across major currency pairs and that the GA-ACD model outperforms the standard generalized gamma ACD model.

Complexity vs Empirical Score

  • Math Complexity: 7.0/10
  • Empirical Rigor: 7.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper introduces a novel GA-ACD model to address a specific empirical phenomenon in FX data using a sophisticated mixture distribution and score-driven dynamics. It combines strong mathematical modeling with a clear empirical application and simulation study, demonstrating both theoretical depth and practical relevance.

Research Flowchart

  flowchart TD
    A[Research Goal: Model Trade Durations & Address Integer Heaping in Forex] --> B{Empirical Observation: Integer Clustering in Durations};
    B --> C[Proposed Solution: Granularity-Adjusted ACD (GA-ACD) Model];
    C --> D{Model Components: Generalized Gamma + Heaping Component + Score-Driven Dynamics};
    D --> E[Computational Process: Maximum Likelihood Estimation & Simulation Study];
    E --> F[Data/Inputs: High-Frequency Forex Trade Data];
    F --> G[Key Outcomes: GA-ACD Outperforms Standard ACD; Heaping Causes Biased Estimates];